Agentic AI Engineer – AWS Bedrock, LangGraph, RAG & Multi-Agent Systems
Synechron (company site, opens in a new tab)3–5 yrsPuneOn-siteDirect career pageEst. 12–20 LPA
Posted 2d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and scale multi-agent orchestration frameworks and RAG systems using AWS Bedrock for autonomous AI workflows automating complex business processes.
- Build and maintain AI systems including planners, executors, memory systems, tool integrations, secure serverless workflows, and data ingestion pipelines enhancing decision support and operational efficiency.
- Implement LLMOps best practices, safety guardrails, semantic search, and evaluation datasets to deliver secure, scalable, measurable, and maintainable enterprise AI solutions.
Minimum Requirements
- 3–5+ years of core software development experience with at least 1–2 years focused on production-level LLM and agentic AI workflows.
- Expert proficiency in Python and asynchronous backend API frameworks like FastAPI or Flask.
- Experience with AWS Bedrock and related AWS services (EC2, Lambda, IAM, VPCs, Step Functions).
- Experience with agent orchestration frameworks (e.g., LangGraph, CrewAI), RAG architectures, vector databases, and semantic search technologies.
Ideal Candidate Profile
- Experienced in designing multi-agent systems, autonomous task execution engines, and complex AI workflows within enterprise or regulated environments.
- Practical expertise translating complex business processes into deterministic, code-driven technical workflows with measurable outcomes.
- Skilled in integrating secure AI components, implementing safety guardrails, and optimizing AI systems for scalability, cost, and reliability using AWS cloud services and LLMOps methodologies.